DOI : 10.1055/s-00000012

Endoscopy

Issue S 01 · Volume 52 · April 2020 DOI: 10.1055/s-010-48290

ESGE
ESGE Days
Dublin, Ireland, 23.-25.04.2020

Mário Dinis-Ribeiro
Abstracts (HTML) Abstracts (PDF) List of Authors
OP54
Abdelrahim, M; Saiko, M; Masaike, Y; Arndtz, S; Hossain, E; Bhandari, P: PIXEL VS PATCH-BASED DEEP LEARNING MODELS, PAVING THE WAY TOWARDS REAL-TIME AI-ASSISTED DETECTION OF BARRETT’S NEOPLASIA
OP55V
Ebigbo, A; Mendel, R; Tziatzios, G; Probst, A; Palm, C; Messmann, H: REAL-TIME DIAGNOSIS OF AN EARLY BARRETT’S CARCINOMA USING ARTIFICIAL INTELLIGENCE (AI) - VIDEO CASE DEMONSTRATION
OP56
Cherciu Harbiyeli, IF; Cazacu, IM; Ivan, ET; Serbanescu, MS; Hurezeanu, B; Saftoiu, A: ARTIFICIAL INTELLIGENCE IN ENDOSCOPY FOR GASTRIC CANCER ASSESSMENT: MACHINE OVER MAN OR PERFECT HARMONY?
OP57
Choi, SJ; Choi, HS; Khan, A; Choo, J; Lee, KW; Kim, S; Jeon, HJ; Lee, JM; Kim, ES; Keum, B; Jeen, YT; Chun, HJ; Lee, HS; Kim, CD: DEVELOPMENT AND VALIDATION OF ARTIFICIAL INTELLIGENCE PROGRAM USING THE STANDARD 8 REGION IMAGING METHOD FOR THE QUALITY CONTROL OF ESOPHAGODUODENOGASTROSCOPY
OP58
Seibt, H; Beyer, A; Häfner, M; Eggert, C; Huber, H; Rath, T: EVALUATION OF A REAL-TIME ARTIFICIAL INTELLIGENCE SYSTEM USING A DEEP NEURAL NETWORK FOR POLYP DETECTION AND LOCALIZATION IN THE LOWER GASTROINTESTINAL TRACT
OP59
Schreuder, RM; van der Zander, QEW.; Fonellà, Roger; Smyl, M; de With, PHN; van der Sommen, F; Schoon, EJ: ALGORITHM COMBINING VIRTUAL CHROMOENDOSCOPY FEATURES FOR POLYP CLASSIFICATION
OP60
Hassan, C; Sharma, P; Wallace, M; Rösch, T; Badalamenti, M; Maselli, R; Spadaccini, M; Bhandari, P; Fugazza, A; Lamonaca, L; Pellegatta, G; Alkandari, A; Capogreco, A; Galtieri, PA; Carrara, S; Leo, MD; Anderloni, A; Repici, A: MISS RATE DUE TO FAILURE RECOGNITION: ARTIFICIAL INTELLIGENCE ESTIMATE BASED ON A HIGH-QUALITY. A RANDOMIZED CLINICAL TRIAL
OP61
Eelbode, T; Hassan, C; Neumann, H; Demedts, I; Sinonquel, P; Roelandt, P; Camps, C; Coron, E; Bhandari, P; Pech, O; Willekens, H; Maes, F; Bisschops, R: A PROSPECTIVE, MULTI-CENTER VALIDATION STUDY FOR AUTOMATED POLYP DETECTION AS A SECOND OBSERVER
OP62
Stammers, M; Thayalasekaran, S; Abdelrahim, M; Bhandari, P: DEVELOPMENT OF MACHINE LEARNING MODELS TO PREDICT RISK OF PATHOLOGY OR NEED FOR INTERVENTION AMONGST ADULT PATIENTS UNDERGOING COLONOSCOPY
OP63
Neumann, H; Sivanathan, V; Rahman, F; Galle, PR: ARTIFICIAL INTELLIGENCE COMBINED WITH LCI YIELDS IN HIGHEST ACCURACY AND DETECTION OF COLORECTAL POLYPS, INCLUDING SESSILE SERRATED LESIONS
OP64
Park, J; Hwang, Y; Lim, YJ; Nam, JH; Oh, DJ; Kim, KB; Song, HJ; Kim, SH; Jung, MK: ARTIFICIAL INTELLIGENCE, TRAINED WITH A ROUGH BINARY CLASSIFICATION, CAN SELECT SIGNIFICANT IMAGES OF CAPSULE ENDOSCOPY
OP65
Romańczyk, M; Ostrowski, B; Romańczyk, T; Marek, T; Błaszczyńska, M; Koziej, M; Waluga, M; Hartleb, M: RECENT UPPER GASTROINTESTINAL ENDOSCOPY QUALITY MEASURES SEEM TO BE USEFUL BUT NEED FURTHER VALIDATION. A MULTICENTER OBSERVATIONAL STUDY